Answers for "how to read and write a file in python"

python write to file

file = open(“testfile.txt”,”w”) 
 
file.write(“Hello World”) 
file.write(“This is our new text file”) 
file.write(“and this is another line.”) 
file.write(“Why? Because we can.”) 
 
file.close() 

python read file

# Basic syntax:
with open('/path/to/filename.extension', 'open_mode') as filename:
  file_data = filename.readlines()	# Or filename.read() 
# Where:
#	- open imports the file as a file object which then needs to be read
#		with one of the read options
#	- readlines() imports each line of the file as an element in a list
#	- read() imports the file contents as one long new-line-separated 
#		string
#	- open_mode can be one of:
#		- "r" = Read which opens a file for reading (error if the file 
#			doesn't exist)
#		- "a" = Append which opens a file for appending (creates the 
#			file if it doesn't exist)
#		- "w" = Write which opens a file for writing (creates the file 
#			if it doesn't exist)
#		- "x" = Create which creates the specified file (returns an error
#			if the file exists)
# Note, "with open() as" is recommended because the file is closed 
#	automatically so you don't have to remember to use file.close()

# Basic syntax for a delimited file with multiple fields:
import csv
with open('/path/to/filename.extension', 'open_mode') as filename:
	file_data = csv.reader(filename, delimiter='delimiter')
    data_as_list = list(file_data)
# Where:
#	- csv.reader can be used for files that use any delimiter, not just
#		commas, e.g.: 't', '|', ';', etc. (It's a bit of a misnomer)
#	- csv.reader() returns a csv.reader object which can be iterated 
#		over, directly converted to a list, and etc. 

# Importing data using Numpy:
import numpy as np
data = np.loadtxt('/path/to/filename.extension',
				delimiter=',', 	# String used to separate values
				skiprows=2, 	# Number of rows to skip
				usecols=[0,2], 	# Specify which columns to read
				dtype=str) 		# The type of the resulting array

# Importing data using Pandas:
import pandas as pd
data = pd.read_csv('/path/to/filename.extension',
				nrows=5, 		# Number of rows of file to read
				header=None, 	# Row number to use as column names 
	            sep='t', 		# Delimiter to use 
	            comment='#', 	# Character to split comments
				na_values=[""])	# String to recognize as NA/NaN

# Note, pandas can also import excel files with pd.read_excel()

python write to file

with open(filename,"w") as f:
  f.write('Hello World')

python write to file

with open("test.txt",'w',encoding = 'utf-8') as f:
   f.write("my first filen")
   f.write("This filenn")
   f.write("contains three linesn")

python write to file

# using 'with' block

with open("xyz.txt", "w") as file: # xyz.txt is filename, w means write format
  file.write("xyz") # write text xyz in the file
  
# maunal opening and closing

f= open("xyz.txt", "w")
f.write("hello")
f.close()

# Hope you had a nice little IO lesson

python write to file

path = "guide/README.txt" # The path of your file should go here
with open(path, "w") as fil: # Opens the file using 'w' method. See below for list of methods.
  fil.write("This is the README. It is reccomended that you read it.") # Writes to the file used .write() method
  fil.close() # Closes file
'''
List of methods:
w* - replace everything with needed text
r^ - read the file
a* - adds to file
x - creates file

* Creates file if the file at that path does not exist
^ Throws error if file does not exist
'''